Update app.py

app.py

@@ -1,444 +1,493 @@
-import streamlit as st
+import os
 import json
-import zipfile
-import io
-import time
 import requests
-from agents import TopicAgent, ContentAgent, SlideAgent, CodeAgent, DesignAgent, VoiceoverAgent
-
-# Initialize agents
-topic_agent = TopicAgent()
-content_agent = ContentAgent()
-slide_agent = SlideAgent()
-code_agent = CodeAgent()
-design_agent = DesignAgent()
-voiceover_agent = VoiceoverAgent()
-
-# =====================
-# STREAMLIT APPLICATION
-# =====================
-
-st.set_page_config(
-    page_title="Workshop in a Box Pro",
-    layout="wide",
-    page_icon="🎓"
-)
-
-# Custom CSS for permanent visibility
-st.markdown("""
-<style>
-    /* Permanent visibility styles */
-    .workshop-container {
-        background: rgba(255, 255, 255, 0.05);
-        border-radius: 10px;
-        padding: 25px;
-        margin-bottom: 20px;
-        border: 1px solid #0d8bf2;
-        box-shadow: 0 4px 20px rgba(0,0,0,0.25);
-    }
-    
-    .section-header {
-        border-left: 4px solid #0d8bf2;
-        padding-left: 15px;
-        margin-top: 10px;
-        margin-bottom: 20px;
-    }
-    
-    .executive-summary {
-        background: linear-gradient(to right, #1a2980, #26d0ce);
-        padding: 25px;
-        border-radius: 15px;
-        margin-bottom: 25px;
-        box-shadow: 0 10px 20px rgba(0,0,0,0.2);
-    }
-    
-    /* Override expander styles */
-    .stApp {
-        background: linear-gradient(135deg, #0f2027 0%, #203a43 100%);
-        color: #fff;
-        font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
-    }
-    
-    .stTextInput>div>div>input {
-        background-color: rgba(255,255,255,0.1) !important;
-        color: white !important;
-        border: 1px solid #4CAF50;
-        border-radius: 8px;
-    }
-    
-    .stButton>button {
-        background: linear-gradient(to right, #0d8bf2, #04befe) !important;
-        color: white !important;
-        border: none;
-        border-radius: 8px;
-        padding: 12px 30px;
-        font-size: 16px;
-        font-weight: bold;
-        box-shadow: 0 4px 6px rgba(0,0,0,0.1);
-        transition: all 0.3s ease;
-    }
-    
-    .stDownloadButton>button {
-        background: linear-gradient(to right, #00c853, #64dd17) !important;
-    }
-    
-    .premium-badge {
-        background: linear-gradient(45deg, #ffd700, #ff9800);
-        color: #000;
-        padding: 3px 10px;
-        border-radius: 12px;
-        font-size: 0.8em;
-        font-weight: bold;
-        display: inline-block;
-        margin-left: 10px;
-    }
-    
-    .pricing-card {
-        background: rgba(255,255,255,0.05);
-        border-radius: 10px;
-        padding: 20px;
-        margin: 10px 0;
-        border: 1px solid #0d8bf2;
-    }
-    
-    .testimonial {
-        background: rgba(255,255,255,0.05);
-        border-radius: 10px;
-        padding: 15px;
-        margin: 15px 0;
-        border-left: 4px solid #00c853;
-    }
-    
-    .disabled-widget {
-        opacity: 0.6;
-        pointer-events: none;
-    }
-</style>
-""", unsafe_allow_html=True)
-
-# Header
-col1, col2 = st.columns([1, 4])
-with col1:
-    st.image("https://cdn-icons-png.flaticon.com/512/1995/1995485.png", width=80)
-with col2:
-    st.title("🤖 Workshop in a Box Pro")
-    st.markdown("Generate Boardroom-Quality Corporate Training <span class='premium-badge'>PREMIUM</span>", unsafe_allow_html=True)
-    st.caption("Create $10K+ Value Workshops in Minutes")
-
-# Initialize session state
-if 'workshop_topic' not in st.session_state:
-    st.session_state.workshop_topic = "AI-Driven Business Transformation"
-if 'generated' not in st.session_state:
-    st.session_state.generated = False
-if 'generating' not in st.session_state:
-    st.session_state.generating = False
-if 'voiceovers' not in st.session_state:
-    st.session_state.voiceovers = {}
-if 'selected_voice' not in st.session_state:
-    st.session_state.selected_voice = "21m00Tcm4TlvDq8ikWAM"
-if 'duration' not in st.session_state:
-    st.session_state.duration = 4.0
-if 'difficulty' not in st.session_state:
-    st.session_state.difficulty = "C-Suite"
-if 'include_code' not in st.session_state:
-    st.session_state.include_code = True
-if 'include_design' not in st.session_state:
-    st.session_state.include_design = True
-if 'include_voiceover' not in st.session_state:
-    st.session_state.include_voiceover = True
-if 'premium_mode' not in st.session_state:
-    st.session_state.premium_mode = True
-
-# Sidebar configuration
-with st.sidebar:
-    st.header("⚙️ Executive Workshop Configuration")
-    st.session_state.workshop_topic = st.text_input(
-        "Workshop Focus", 
-        st.session_state.workshop_topic,
-        help="Strategic business topic (e.g., 'AI for Financial Services Transformation')"
-    )
-    
-    topic_empty = st.session_state.workshop_topic.strip() == ""
-    
-    if topic_empty:
-        st.warning("Please enter a strategic workshop focus to enable configuration")
-    
-    st.session_state.duration = st.slider(
-        "Duration (hours)", 
-        2.0, 8.0, st.session_state.duration, 0.5, 
-        help="Full-day or half-day workshop",
-        disabled=topic_empty
-    )
-    
-    st.session_state.difficulty = st.selectbox(
-        "Audience Level", 
-        ["C-Suite", "Executives", "Directors", "Managers"],
-        index=["C-Suite", "Executives", "Directors", "Managers"].index(st.session_state.difficulty),
-        disabled=topic_empty
-    )
-    
-    st.session_state.include_code = st.checkbox(
-        "Include Technical Implementation", 
-        st.session_state.include_code,
-        disabled=topic_empty
-    )
-    
-    st.session_state.include_design = st.checkbox(
-        "Generate Premium Visuals", 
-        st.session_state.include_design,
-        disabled=topic_empty
-    )
-    
-    st.session_state.include_voiceover = st.checkbox(
-        "Generate Voiceovers", 
-        st.session_state.include_voiceover,
-        disabled=topic_empty
-    )
-    
-    if st.session_state.include_voiceover and not topic_empty:
-        st.subheader("🎙️ Voice Selection")
-        voices = voiceover_agent.get_voices()
-        
-        if voices:
-            selected_voice = st.selectbox(
-                "Choose a voice:",
-                options=[v['voice_id'] for v in voices],
-                format_func=lambda id: next((v['name'] for v in voices if v['voice_id'] == id), "Default"),
-                key="voice_select"
+from dotenv import load_dotenv
+from openai import OpenAI
+from flask import Flask, render_template_string, request
+
+# Load environment variables
+load_dotenv()
+
+# Initialize API clients
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+openai_client = OpenAI(api_key=OPENAI_API_KEY) if OPENAI_API_KEY else None
+ELEVENLABS_API_KEY = os.getenv("ELEVENLABS_API_KEY")
+
+app = Flask(__name__)
+
+# ---------- Agent implementations ----------
+
+class TopicAgent:
+    def generate_outline(self, topic, duration, difficulty):
+        if not openai_client:
+            print("OpenAI API not set - using enhanced mock data for outline.")
+            return self._mock_outline(topic, duration, difficulty)
+
+        try:
+            response = openai_client.chat.completions.create(
+                model="gpt-4-turbo",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": (
+                            "You are an expert corporate trainer with 20+ years of experience creating "
+                            "high-value workshops for Fortune 500 companies. Create a professional workshop outline that "
+                            "includes: 1) Clear learning objectives, 2) Practical real-world exercises, "
+                            "3) Industry case studies, 4) Measurable outcomes. Format as JSON."
+                        )
+                    },
+                    {
+                        "role": "user",
+                        "content": (
+                            f"Create a comprehensive {duration}-hour {difficulty} workshop outline on '{topic}' for corporate executives. "
+                            "Structure: title, duration, difficulty, learning_goals (3-5 bullet points), "
+                            "modules (5-7 modules). Each module should have: title, duration, learning_points (3 bullet points), "
+                            "case_study (real company example), exercises (2 practical exercises)."
+                        )
+                    }
+                ],
+                temperature=0.3,
+                max_tokens=1500,
+                response_format={"type": "json_object"}
+            )
+            return json.loads(response.choices[0].message.content)
+        except Exception as e:
+            print(f"Error during OpenAI outline generation: {e}. Falling back to mock outline.")
+            return self._mock_outline(topic, duration, difficulty)
+
+    def _mock_outline(self, topic, duration, difficulty):
+        return {
+            "title": f"Mastering {topic} for Business Impact",
+            "duration": f"{duration} hours",
+            "difficulty": difficulty,
+            "learning_goals": [
+                "Apply advanced techniques to real business challenges",
+                "Measure ROI of prompt engineering initiatives",
+                "Develop organizational prompt engineering standards",
+                "Implement ethical AI governance frameworks"
+            ],
+            "modules": [
+                {
+                    "title": "Strategic Foundations",
+                    "duration": "45 min",
+                    "learning_points": [
+                        "Business value assessment framework",
+                        "ROI calculation models",
+                        "Stakeholder alignment strategies"
+                    ],
+                    "case_study": "How JPMorgan reduced operational costs by 37% with prompt optimization",
+                    "exercises": [
+                        "Calculate potential ROI for your organization",
+                        "Develop stakeholder communication plan"
+                    ]
+                },
+                {
+                    "title": "Advanced Pattern Engineering",
+                    "duration": "60 min",
+                    "learning_points": [
+                        "Chain-of-thought implementations",
+                        "Self-correcting prompt architectures",
+                        "Domain-specific pattern libraries"
+                    ],
+                    "case_study": "McKinsey's knowledge management transformation",
+                    "exercises": [
+                        "Design pattern library for your industry",
+                        "Implement self-correction workflow"
+                    ]
+                }
+            ]
+        }
+
+
+class ContentAgent:
+    def generate_content(self, outline):
+        if not openai_client:
+            print("OpenAI API not set - using enhanced mock data for content.")
+            return self._mock_content(outline)
+
+        try:
+            response = openai_client.chat.completions.create(
+                model="gpt-4-turbo",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": (
+                            "You are a senior instructional designer creating premium corporate training materials. "
+                            "Develop comprehensive workshop content with: 1) Practitioner-level insights, "
+                            "2) Actionable frameworks, 3) Real-world examples, 4) Practical exercises. "
+                            "Avoid generic AI content - focus on business impact."
+                        )
+                    },
+                    {
+                        "role": "user",
+                        "content": (
+                            f"Create premium workshop content for this outline: {json.dumps(outline)}. "
+                            "For each module: "
+                            "1) Detailed script (executive summary, 3 key concepts, business applications) "
+                            "2) Speaker notes (presentation guidance) "
+                            "3) 3 discussion questions with executive-level responses "
+                            "4) 2 practical exercises with solution blueprints "
+                            "Format as JSON."
+                        )
+                    }
+                ],
+                temperature=0.4,
+                max_tokens=3000,
+                response_format={"type": "json_object"}
+            )
+            return json.loads(response.choices[0].message.content)
+        except Exception as e:
+            print(f"Error during OpenAI content generation: {e}. Falling back to mock content.")
+            return self._mock_content(outline)
+
+    def _mock_content(self, outline):
+        return {
+            "workshop_title": outline.get("title", "Premium AI Workshop"),
+            "modules": [
+                {
+                    "title": "Strategic Foundations",
+                    "script": (
+                        "## Executive Summary\n"
+                        "This module establishes the business case for advanced prompt engineering, "
+                        "focusing on measurable ROI and stakeholder alignment.\n\n"
+                        "### Key Concepts:\n"
+                        "1. **Value Assessment Framework**: Quantify potential savings and revenue opportunities\n"
+                        "2. **ROI Calculation Models**: Custom models for different industries\n"
+                        "3. **Stakeholder Alignment**: Executive communication strategies\n\n"
+                        "### Business Applications:\n"
+                        "- Cost reduction in customer service operations\n"
+                        "- Acceleration of R&D processes\n"
+                        "- Enhanced competitive intelligence"
+                    ),
+                    "speaker_notes": [
+                        "Emphasize real dollar impact - use JPMorgan case study numbers",
+                        "Show ROI calculator template",
+                        "Highlight C-suite communication strategies"
+                    ],
+                    "discussion_questions": [
+                        {
+                            "question": "How could prompt engineering impact your bottom line?",
+                            "response": "Typical results: 30-40% operational efficiency gains, 15-25% innovation acceleration"
+                        }
+                    ],
+                    "exercises": [
+                        {
+                            "title": "ROI Calculation Workshop",
+                            "instructions": "Calculate potential savings using our enterprise ROI model",
+                            "solution": "Template: (Current Cost × Efficiency Gain) - Implementation Cost"
+                        }
+                    ]
+                }
+            ]
+        }
+
+
+class SlideAgent:
+    def generate_slides(self, content):
+        if not openai_client:
+            print("OpenAI API not set - using enhanced mock slides.")
+            return self._professional_slides(content)
+
+        try:
+            response = openai_client.chat.completions.create(
+                model="gpt-4-turbo",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": (
+                            "You are a McKinsey-level presentation specialist. Create professional slides with: "
+                            "1) Clean, executive-friendly design 2) Data visualization frameworks "
+                            "3) Action-oriented content 4) Brand-compliant styling. "
+                            "Use Marp Markdown format with the 'gaia' theme."
+                        )
+                    },
+                    {
+                        "role": "user",
+                        "content": (
+                            f"Create a boardroom-quality slide deck for: {json.dumps(content)}. "
+                            "Structure: Title slide, module slides (objective, 3 key points, case study, exercise), "
+                            "summary slide. Include placeholders for data visualization."
+                        )
+                    }
+                ],
+                temperature=0.2,
+                max_tokens=2500
+            )
+            return response.choices[0].message.content
+        except Exception as e:
+            print(f"Error during slide generation: {e}. Using mock slides.")
+            return self._professional_slides(content)
+
+    def _professional_slides(self, content):
+        return f"""---
+marp: true
+theme: gaia
+class: lead
+paginate: true
+backgroundColor: #fff
+backgroundImage: url('https://marp.app/assets/hero-background.svg')
+---
+
+# {content.get('workshop_title', 'Executive AI Workshop')}
+## Transforming Business Through Advanced AI
+
+---
+<!-- _class: invert -->
+## Module 1: Strategic Foundations
+### Driving Measurable Business Value
+
+![bg right:40% w:450](https://images.pexels.com/photos/3184292/pexels-photo-3184292.jpeg)
+
+- **ROI Framework**: Quantifying impact
+- **Stakeholder Alignment**: Executive buy-in strategies
+- **Implementation Roadmap**: Phased adoption plan
+
+---
+## Case Study: Financial Services Transformation
+### JPMorgan Chase
+
+| Metric | Before | After | Improvement |
+|--------|--------|-------|-------------|
+| Operation Costs | $4.2M | $2.6M | 38% reduction |
+| Process Time | 14 days | 3 days | 79% faster |
+| Error Rate | 8.2% | 0.4% | 95% reduction |
+
+---
+## Practical Exercise: ROI Calculation
+```mermaid
+graph TD
+    A[Current Costs] --> B[Potential Savings]
+    C[Implementation Costs] --> D[Net ROI]
+    B --> D
+Document current process costs
+
+Estimate efficiency gains
+
+Calculate net ROI
+
+Q&A
+Let's discuss your specific challenges
+```"""
+
+
+class CodeAgent:
+    def generate_code(self, content):
+        if not openai_client:
+            print("OpenAI API not set - using enhanced mock code.")
+            return self._professional_code(content)
+
+        try:
+            response = openai_client.chat.completions.create(
+                model="gpt-4-turbo",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": (
+                            "You are an enterprise solutions architect. Create professional-grade code labs with: "
+                            "1) Production-ready patterns 2) Comprehensive documentation "
+                            "3) Enterprise security practices 4) Scalable architectures. "
+                            "Use Python with the latest best practices."
+                        )
+                    },
+                    {
+                        "role": "user",
+                        "content": (
+                            f"Create a professional code lab for: {json.dumps(content)}. "
+                            "Include: Setup instructions, business solution patterns, "
+                            "enterprise integration examples, and security best practices."
+                        )
+                    }
+                ],
+                temperature=0.3,
+                max_tokens=2500
             )
-            st.session_state.selected_voice = selected_voice
-        elif voiceover_agent.api_key:
-            st.warning("Couldn't load voices. Using default voice.")
-        else:
-            st.warning("ElevenLabs API key not set. Voiceovers disabled.")
-
-    st.divider()
-    st.markdown("**Quality Assurance**")
-    st.session_state.premium_mode = st.checkbox(
-        "Enable Premium Mode", 
-        st.session_state.premium_mode, 
-        help="Generate boardroom-quality content with real-world case studies",
-        disabled=topic_empty
+            return response.choices[0].message.content
+        except Exception as e:
+            print(f"Error during code generation: {e}. Using mock code.")
+            return self._professional_code(content)
+
+    def _professional_code(self, content):
+        return f"""# Enterprise-Grade Prompt Engineering Lab
+# Business Solution Framework
+class PromptOptimizer:
+    def __init__(self, model="gpt-4-turbo"):
+        self.model = model
+        self.pattern_library = {{
+            "financial_analysis": "Extract key metrics from financial reports",
+            "customer_service": "Resolve tier-2 support tickets"
+        }}
+
+    def optimize_prompt(self, business_case):
+        # Implement enterprise optimization logic
+        return f"Business-optimized prompt for {{business_case}}"
+
+    def calculate_roi(self, current_cost, expected_efficiency):
+        return current_cost * expected_efficiency
+
+# Example usage
+optimizer = PromptOptimizer()
+print(optimizer.calculate_roi(500000, 0.35))  # $175,000 savings
+
+# Security Best Practices
+def secure_prompt_handling(user_input):
+    # Implement OWASP security standards
+    sanitized = sanitize_input(user_input)
+    validate_business_context(sanitized)
+    return apply_enterprise_guardrails(sanitized)
+
+# Integration Pattern: CRM System
+def integrate_with_salesforce(prompt, salesforce_data):
+    # Enterprise integration example
+    enriched_prompt = f"{{prompt}} using {{salesforce_data}}"
+    return call_ai_api(enriched_prompt)
+"""
+
+
+class DesignAgent:
+    def generate_design(self, slide_content):
+        if not openai_client:
+            print("OpenAI API not set - skipping design generation.")
+            return None
+
+        try:
+            response = openai_client.images.generate(
+                model="dall-e-3",
+                prompt=(
+                    f"Professional corporate slide background for '{slide_content[:200]}' workshop. "
+                    "Modern business style, clean lines, premium gradient, boardroom appropriate. "
+                    "Include abstract technology elements in corporate colors."
+                ),
+                n=1,
+                size="1024x1024"
+            )
+            return response.data[0].url
+        except Exception as e:
+            print(f"Error during design generation: {e}.")
+            return None
+
+
+class VoiceoverAgent:
+    def __init__(self):
+        self.api_key = ELEVENLABS_API_KEY
+        self.voice_id = "21m00Tcm4TlvDq8ikWAM"  # Default voice ID
+        self.model = "eleven_monolingual_v1"
+
+    def generate_voiceover(self, text, voice_id=None):
+        if not self.api_key:
+            print("ElevenLabs API key not set - skipping voiceover generation.")
+            return None
+
+        try:
+            voice = voice_id if voice_id else self.voice_id
+            url = f"https://api.elevenlabs.io/v1/text-to-speech/{voice}"
+            headers = {
+                "Accept": "audio/mpeg",
+                "Content-Type": "application/json",
+                "xi-api-key": self.api_key
+            }
+            data = {
+                "text": text,
+                "model_id": self.model,
+                "voice_settings": {
+                    "stability": 0.7,
+                    "similarity_boost": 0.8,
+                    "style": 0.5,
+                    "use_speaker_boost": True
+                }
+            }
+            response = requests.post(url, json=data, headers=headers)
+            response.raise_for_status()
+            return response.content
+        except requests.exceptions.RequestException as e:
+            print(f"Error generating voiceover: {e}")
+            return None
+
+    def get_voices(self):
+        if not self.api_key:
+            print("ElevenLabs API key not set - cannot fetch voices.")
+            return []
+
+        try:
+            url = "https://api.elevenlabs.io/v1/voices"
+            headers = {"xi-api-key": self.api_key}
+            response = requests.get(url, headers=headers)
+            response.raise_for_status()
+            return response.json().get("voices", [])
+        except requests.exceptions.RequestException as e:
+            print(f"Error fetching voices: {e}")
+            return []
+
+
+# ---------- Simple frontend to show workshop focus input ----------
+
+HTML_PAGE = """
+<!doctype html>
+<html lang="en">
+<head>
+  <meta charset="utf-8" />
+  <title>Executive Workshop Configuration</title>
+  <meta name="viewport" content="width=device-width,initial-scale=1" />
+  <style>
+    body { font-family: system-ui,-apple-system,BlinkMacSystemFont,sans-serif; background:#f0f4f8; padding:30px; }
+    .card { background:#fff; padding:20px; border-radius:12px; max-width:500px; margin:auto; box-shadow:0 10px 25px rgba(0,0,0,0.05); }
+    h1 { font-size:1.75rem; margin-bottom:4px; display:flex; align-items:center; gap:8px; }
+    label { display:block; margin-top:16px; font-weight:600; }
+    input { width:100%; padding:10px 14px; border:1px solid #cbd5e1; border-radius:6px; font-size:1rem; transition: all .2s; color:#1f2937; background:#fff; }
+    input:focus { outline:none; border-color:#2563eb; box-shadow:0 0 0 3px rgba(59,130,246,0.35); }
+    input::placeholder { color:#94a3b8; }
+    ::selection { background: rgba(59,130,246,0.4); color:#000; }
+    .status { margin-bottom:12px; padding:12px; border-radius:8px; }
+    .warn { background:#fff8e1; border:1px solid #f5e1a4; color:#886f1b; }
+    .ok { background:#e6f6ed; border:1px solid #b8e0c5; color:#1e5f3d; }
+    .note { margin-top:8px; font-size:.9rem; color:#475569; }
+  </style>
+</head>
+<body>
+  <div class="card">
+    <div class="status {{ 'ok' if openai_set else 'warn' }}">
+      {% if openai_set %}
+        <div class="ok">OpenAI API Key Found</div>
+      {% else %}
+        <div class="warn">OpenAI API not set - using enhanced mock data</div>
+      {% endif %}
+      {% if elevenlabs_set %}
+        <div class="ok" style="margin-top:6px;">ElevenLabs API Key Found</div>
+      {% else %}
+        <div class="warn" style="margin-top:6px;">ElevenLabs API Key not set</div>
+      {% endif %}
+    </div>
+    <h1>Executive Workshop Configuration</h1>
+    <form method="post" action="/submit">
+      <label for="focus">Workshop Focus</label>
+      <input id="focus" name="focus" placeholder="e.g., AI-Driven Business Transformation" value="{{ prefill }}" autocomplete="off" />
+      <div class="note">Type here to set the workshop's focus. Selection and text are styled for clarity.</div>
+      <button type="submit" style="margin-top:16px; padding:10px 16px; border:none; background:#2563eb; color:#fff; border-radius:6px; cursor:pointer;">Save</button>
+    </form>
+  </div>
+</body>
+</html>
+"""
+
+@app.route("/", methods=["GET"])
+def index():
+    return render_template_string(
+        HTML_PAGE,
+        openai_set=bool(OPENAI_API_KEY),
+        elevenlabs_set=bool(ELEVENLABS_API_KEY),
+        prefill=""
     )
 
-    generate_disabled = topic_empty or st.session_state.generating
-    if st.button(
-        "✨ Generate Premium Workshop", 
-        type="primary", 
-        use_container_width=True,
-        disabled=generate_disabled
-    ):
-        st.session_state.generating = True
-        st.session_state.voiceovers = {}
-
-# Generation pipeline
-if st.session_state.generating and not topic_empty:
-    with st.spinner(f"🚀 Creating your executive workshop on '{st.session_state.workshop_topic}'..."):
-        start_time = time.time()
-        
-        outline = topic_agent.generate_outline(
-            st.session_state.workshop_topic, 
-            st.session_state.duration, 
-            st.session_state.difficulty
-        )
-        content = content_agent.generate_content(outline)
-        slides = slide_agent.generate_slides(content)
-        code_labs = code_agent.generate_code(content) if st.session_state.include_code else None
-        design_url = design_agent.generate_design(slides) if st.session_state.include_design else None
-        
-        voiceovers = {}
-        if st.session_state.include_voiceover and voiceover_agent.api_key:
-            for i, module in enumerate(content.get("modules", [])):
-                intro_text = f"Module {i+1}: {module['title']}. " + \
-                            f"Key concepts: {', '.join(module.get('learning_points', [''])[:3])}"
-                audio_data = voiceover_agent.generate_voiceover(
-                    intro_text,
-                    st.session_state.selected_voice
-                )
-                if audio_data:
-                    voiceovers[f"module_{i+1}_intro.mp3"] = audio_data
-        
-        zip_buffer = io.BytesIO()
-        with zipfile.ZipFile(zip_buffer, "a", zipfile.ZIP_DEFLATED) as zip_file:
-            zip_file.writestr("executive_summary.json", json.dumps(outline, indent=2))
-            zip_file.writestr("workshop_content.json", json.dumps(content, indent=2))
-            zip_file.writestr("boardroom_slides.md", slides)
-            if code_labs:
-                zip_file.writestr("enterprise_solutions.ipynb", code_labs)
-            if design_url:
-                try:
-                    img_data = requests.get(design_url).content
-                    zip_file.writestr("slide_design.png", img_data)
-                except Exception as e:
-                    st.error(f"Design download error: {str(e)}")
-            for filename, audio_data in voiceovers.items():
-                zip_file.writestr(f"voiceovers/{filename}", audio_data)
-        
-        st.session_state.outline = outline
-        st.session_state.content = content
-        st.session_state.slides = slides
-        st.session_state.code_labs = code_labs
-        st.session_state.design_url = design_url
-        st.session_state.voiceovers = voiceovers
-        st.session_state.zip_buffer = zip_buffer
-        st.session_state.gen_time = round(time.time() - start_time, 2)
-        st.session_state.generated = True
-        st.session_state.generating = False
-
-# Results display - PERMANENTLY VISIBLE SECTION
-if st.session_state.generated and not topic_empty:
-    st.success(f"✅ Executive workshop generated in {st.session_state.gen_time} seconds!")
-    
-    st.download_button(
-        label="📥 Download Executive Package",
-        data=st.session_state.zip_buffer.getvalue(),
-        file_name=f"{st.session_state.workshop_topic.replace(' ', '_')}_workshop.zip",
-        mime="application/zip",
-        use_container_width=True
+@app.route("/submit", methods=["POST"])
+def submit():
+    focus = request.form.get("focus", "")
+    # For demo: echo back with prefill
+    return render_template_string(
+        HTML_PAGE,
+        openai_set=bool(OPENAI_API_KEY),
+        elevenlabs_set=bool(ELEVENLABS_API_KEY),
+        prefill=focus
     )
-    
-    # Executive summary - ALWAYS VISIBLE
-    st.markdown("<div class='section-header'><h2>📊 Executive Overview</h2></div>", unsafe_allow_html=True)
-    st.markdown(f"<div class='executive-summary'>", unsafe_allow_html=True)
-    st.subheader(st.session_state.outline.get("title", "Strategic Workshop"))
-    st.caption(f"Duration: {st.session_state.outline.get('duration', '4 hours')} | Level: {st.session_state.outline.get('difficulty', 'Executive')}")
-    
-    st.markdown("**Business Value Proposition**")
-    if "learning_goals" in st.session_state.outline:
-        for goal in st.session_state.outline["learning_goals"]:
-            st.markdown(f"- {goal}")
-    
-    st.markdown("**Key Deliverables**")
-    st.markdown("- Boardroom-ready presentation\n"
-                "- Implementation toolkit\n"
-                "- ROI calculation framework\n"
-                "- Enterprise integration guide")
-    st.markdown("</div>", unsafe_allow_html=True)
-
-    # Workshop content - ALWAYS VISIBLE
-    st.markdown("<div class='section-header'><h2>📝 Strategic Content Framework</h2></div>", unsafe_allow_html=True)
-    st.markdown("<div class='workshop-container'>", unsafe_allow_html=True)
-    if "modules" in st.session_state.content:
-        for module in st.session_state.content["modules"]:
-            st.subheader(module.get("title", "Business Module"))
-            st.markdown(module.get("script", ""))
-            
-            st.markdown("**Executive Discussion Points**")
-            if "discussion_questions" in module:
-                for q in module["discussion_questions"]:
-                    st.markdown(f"- **{q.get('question', '')}**")
-                    st.caption(q.get("response", ""))
-            st.divider()
-    st.markdown("</div>", unsafe_allow_html=True)
-
-    # Slide preview - ALWAYS VISIBLE
-    st.markdown("<div class='section-header'><h2>🖥️ Boardroom Presentation Preview</h2></div>", unsafe_allow_html=True)
-    st.markdown("<div class='workshop-container'>", unsafe_allow_html=True)
-    st.markdown(st.session_state.slides[:2000])
-    st.markdown("</div>", unsafe_allow_html=True)
-
-    # Technical implementation - ALWAYS VISIBLE
-    if st.session_state.code_labs:
-        st.markdown("<div class='section-header'><h2>💻 Enterprise Implementation Toolkit</h2></div>", unsafe_allow_html=True)
-        st.markdown("<div class='workshop-container'>", unsafe_allow_html=True)
-        st.code(st.session_state.code_labs)
-        st.markdown("</div>", unsafe_allow_html=True)
-
-    # Design preview - ALWAYS VISIBLE
-    if st.session_state.design_url:
-        st.markdown("<div class='section-header'><h2>🎨 Premium Visual Design</h2></div>", unsafe_allow_html=True)
-        st.markdown("<div class='workshop-container'>", unsafe_allow_html=True)
-        try:
-            st.image(st.session_state.design_url, caption="Corporate Slide Design")
-        except:
-            st.warning("Design preview unavailable")
-        st.markdown("</div>", unsafe_allow_html=True)
-    
-    # Voiceover player - ALWAYS VISIBLE
-    if st.session_state.voiceovers:
-        st.markdown("<div class='section-header'><h2>🔊 Voiceover Previews</h2></div>", unsafe_allow_html=True)
-        st.markdown("<div class='workshop-container'>", unsafe_allow_html=True)
-        for i, (filename, audio_bytes) in enumerate(st.session_state.voiceovers.items()):
-            module_num = filename.split("_")[1]
-            st.subheader(f"Module {module_num} Introduction")
-            st.audio(audio_bytes, format="audio/mp3")
-        st.markdown("</div>", unsafe_allow_html=True)
-
-# Pricing section - ALWAYS VISIBLE
-st.markdown("<div class='section-header'><h2>🚀 Premium Corporate Offering</h2></div>", unsafe_allow_html=True)
-st.markdown(f"""
-### {st.session_state.workshop_topic} Executive Program
-<div class="pricing-card">
-    <h4>Live Workshop</h4>
-    <h2>$15,000</h2>
-    <p>Full-day session with Q&A</p>
-</div>
-<div class="pricing-card">
-    <h4>On-Demand Course</h4>
-    <h2>$7,500</h2>
-    <p>Enterprise-wide access</p>
-</div>
-<div class="pricing-card">
-    <h4>Implementation Package</h4>
-    <h2>$12,500</h2>
-    <p>Technical integration support</p>
-</div>
-
-**Premium Features:**
-- Customized to your industry vertical
-- ROI guarantee
-- 12-month support agreement
-- Executive briefing package
-""", unsafe_allow_html=True)
-
-# Testimonials - ALWAYS VISIBLE
-st.markdown("<div class='section-header'><h2>💼 Executive Testimonials</h2></div>", unsafe_allow_html=True)
-st.markdown("""
-<div class="testimonial">
-    <p>"This platform helped us create a $50K training program in one afternoon. The ROI was immediate."</p>
-    <p><strong>— Sarah Johnson, CLO at FinTech Global</strong></p>
-</div>
-<div class="testimonial">
-    <p>"The boardroom-quality materials impressed our clients and justified our premium pricing."</p>
-    <p><strong>— Michael Chen, Partner at McKinsey & Company</strong></p>
-</div>
-""", unsafe_allow_html=True)
-
-# CTA - ALWAYS VISIBLE
-st.markdown("<div class='section-header'><h2>Get Started</h2></div>", unsafe_allow_html=True)
-col1, col2 = st.columns(2)
-with col1:
-    st.link_button("📅 Book Strategy Session", "https://calendly.com/your-link", use_container_width=True)
-with col2:
-    st.link_button("💼 Enterprise Solutions", "https://your-company.com/enterprise", use_container_width=True)
-
-# Footer - ALWAYS VISIBLE
-st.markdown("""
-<div style="text-align: center; padding: 20px; color: #aaa; margin-top: 30px;">
-    Workshop in a Box Pro® | Enterprise-Grade AI Training Solutions | © 2025
-</div>
-""", unsafe_allow_html=True)
-
-# Debug info - ALWAYS VISIBLE
-with st.sidebar:
-    st.divider()
-    if hasattr(topic_agent, 'openai_client') and topic_agent.openai_client:
-        st.success("OpenAI API Connected")
-    else:
-        st.warning("OpenAI API not set - using enhanced mock data")
-    
-    if voiceover_agent.api_key:
-        st.success("ElevenLabs API Key Found")
-    elif st.session_state.include_voiceover:
-        st.warning("ElevenLabs API key not set")
-    
-    st.info(f"""
-    **Current Workshop:**
-    {st.session_state.workshop_topic}
-    
-    **Premium Features:**
-    - AI-generated voiceovers
-    - Professional slide designs
-    - Real-world case studies
-    - Practical code labs
-    """)
+
+if __name__ == "__main__":
+    print(f"Loaded OPENAI_API_KEY: {bool(OPENAI_API_KEY)}, ELEVENLABS_API_KEY: {bool(ELEVENLABS_API_KEY)}")
+    app.run(host="0.0.0.0", port=8080, debug=True)